arXiv:2602.09123v1 Announce Type: new Abstract: Legged robot research is presently focused on bipedal or quadrupedal robots, despite capabilities to build robots with many more legs to potentially improve locomotion performance. This imbalance is not necessarily due to hardware limitations, but rather to the absence of principled control frameworks that explain when and how additional legs improve locomotion performance. In multi-legged systems, coordinating many simultaneous contacts introduces a severe curse of dimensionality that challenges existing modeling and control approaches. […]

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arXiv:2602.06134v1 Announce Type: new Abstract: In human conversation, empathic dialogue requires nuanced temporal cues indicating whether the conversational partner is paying attention. This type of “active listening” is overlooked in the design of Conversational Agents (CAs), which use the same pacing for one conversation. To model the temporal cues in human conversation, we need CAs that dynamically adjust response pacing according to user input. We qualitatively analyzed ten cases of active listening to distill five context-aware pacing strategies: […]

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arXiv:2602.09720v1 Announce Type: new Abstract: Data streams are rarely static in dynamic environments like Industry 4.0. Instead, they constantly change, making traditional offline models outdated unless they can quickly adjust to the new data. This need can be adequately addressed by continual learning (CL), which allows systems to gradually acquire knowledge without incurring the prohibitive costs of retraining them from scratch. Most research on continual learning focuses on classification problems, while very few studies address regression tasks. We […]

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In-context reinforcement learning (ICRL) promises fast adaptation to unseen environments without parameter updates, but current methods either cannot improve beyond the training distribution or require near-optimal data, limiting practical adoption. We introduce SPICE, a Bayesian ICRL method that learns a prior over Q-values via deep ensemble and updates this prior at test-time using in-context information through Bayesian updates. To recover from poor priors resulting from training on sub-optimal data, our online inference follows an Upper-Confidence Bound rule that […]

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arXiv:2601.12169v1 Announce Type: new Abstract: Deep learning and model predictive control (MPC) can play complementary roles in legged robotics. However, integrating learned models with online planning remains challenging. When dynamics are learned with neural networks, three key difficulties arise: (1) stiff transitions from contact events may be inherited from the data; (2) additional non-physical local nonsmoothness can occur; and (3) training datasets can induce non-Gaussian model errors due to rapid state changes. We address (1) and (2) by […]

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arXiv:2603.00586v1 Announce Type: new Abstract: Production-ready human video generation requires digital actors to maintain strictly consistent full-body identities across dynamic shots, viewpoints and motions, a setting that remains challenging for existing methods. Prior methods often suffer from face-centric behavior that neglects body-level consistency, or produce copy-paste artifacts where subjects appear rigid due to pose locking. We present Actor-18M, a large-scale human video dataset designed to capture identity consistency under unconstrained viewpoints and environments. Actor-18M comprises 1.6M videos with […]

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Key Highlights: As 2025 is coming to an end, more and more online platforms have released their specific year-in-review. Here I’m talking about Spotify Wrapped, Google’s Year in Search, Snapchat Recap, and more. OpenAI, meanwhile, is an AI company, but it isn’t shying away from joining the bandwagon and has released its own version called “Your Year with ChatGPT.” ChatGPT users can get personalized year in review, but it’s limited to select regions now As the name suggests, […]

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Watts critiques our scholastic obsessions and urges an experiential approach to life, blending the spiritual and concrete like a Zen gardener planting mysteries among truths. He laments our sterile materialism and bureaucratic rigidity, championing a dance with risk, creativity, and nonverbal wisdom. With tales of mystics, scientists, and madmen, he celebrates the spice of oddballs, the necessity of nonsense, and the ineffable richness of being alive.

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TIL: SQL functions in Google Sheets to fetch data from Datasette I put together some notes on patterns for fetching data from a Datasette instance directly into Google Sheets – using the importdata() function, a “named function” that wraps it or a Google Apps Script if you need to send an API token in an HTTP header (not supported by importdata().) Here’s an example sheet demonstrating all three methods. Tags: spreadsheets, datasette, google

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